首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Effect of Different Pollution Parameters and Chemical Components of PM2.5 on Health of Residents of Xinxiang City China
【2h】

Effect of Different Pollution Parameters and Chemical Components of PM2.5 on Health of Residents of Xinxiang City China

机译:PM2.5不同污染参数及化学成分对新乡市居民健康的影响

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM2.5) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April–May), 19 (July–August), 27 (September–October), 28 (December–January) of PM2.5 were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM2.5 were analyzed via ion chromatography and inductively coupled plasma–mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM2.5 concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017–2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM2.5 concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM2.5 to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO3−) and sulfate (SO42−) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM2.5 in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM2.5 has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM2.5 rises by 10 μg·m−3, hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741–11.264) and 0.068% (95% CI, 0.067–0.069). GAM model analysis predicted the maximum effect of PM2.5 exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM2.5 on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM2.5 has the greatest effect on HGB. The maximum cumulative effect of PM2.5 on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM2.5 increases significantly and has a significant correlation with some blood routine indicators.
机译:本研究计划,探索污染特征,健康风险,以及大气细颗粒物(PM2.5)和它在一个典型的工业城市(新乡市)在中国血常规参数成分的影响。在本研究中,在2017年至2018年的不同季节收集了102个有效的样品,19(7月至8月),27(9月至8月),28(9月至10月),28(九月至十月),28(12月至1月)。通过离子色谱法和电感耦合等离子体质谱分析PM2.5中的溶解离子和金属元素。从一月不同污染气象条件下的血常规体检参数到十二月2017年2018年,相应的PM2.5浓度,温度和相对湿度在同一时期在2017至18年从新乡市第二人民医院收集。使用广义添加剂时间序列模型(GAM)进行风险评估。它用于分析PM2.5浓度及其组分对体检人群血液常规指标的影响。 R.3.5.3中的“MGCV”包装统计软件用于建模和分析,并用于对温度和湿度等气象指标进行非参数平滑。当Akaike的信息标准(AIC)值最小时,模型的拟合的良好最高。此外,美国EPA暴露模型用于通过呼吸道途径评估PM2.5中不同重金属引起的健康风险,包括呼吸道途径,包括致癌风险和非致癌风险。结果表明,与冬季整体潮流的其他季节相比,新乡市的空气颗粒物质及其化学成分较高>春季>秋季>夏季。冬季大气中硝酸盐(NO 3-)和硫酸盐(SO42-)离子的含量较高,该含量与铵共同构成新乡市PM2.5中水溶性离子的主要成分。源分析报告称,与固定来源相比,新乡市新乡市的移动污染源(煤炭燃烧排放,汽车废气排放和工业排放)促成了大气污染。风险评估结果表明,人体中,人体中重金属的非致癌物质的风险是可以接受的,而致癌元素中的致癌风险的顺序是砷(AS)>铬(CR) >镉(CD)>钴(CO)>镍(Ni)。在雾度污染期间,PM2.5的暴露浓度对血液常规参数具有一定的滞后效应。当雾度污染发生时,当PM2.5的每日平均浓度上升10μg·m-3时,血红蛋白(HgB)和血小板计数(PLT)分别增加9.923%(95%CI,8.741- 11.264)和0.068%(95%CI,0.067-0.069)。 GAM模型分析预测PM2.5暴露浓度对红细胞计数(RBC)的最大效果,并且当滞后累积1D(LAG0)时达到PLT。当滞后累积为3D时,达到了PM2.5对单声道的暴露浓度的最大效果。当滞后累积6D(LAG5)时,PM2.5的曝光浓度对HGB具有最大的影响。当滞后为2D(LAG1)时,PM2.5对中性粒细胞计数(中性)和淋巴细胞(LMY)的最大累积效果最强。在中度至严重污染期间,PM2.5中水溶性离子和重金属元素的浓度显着增加,与一些血液常规指标具有显着的相关性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号